code: def general_cosine(
      M,
      *,
      a: Iterable,
      sym: bool = True,
      dtype: Optional[torch.dtype] = None,
      layout: torch.layout = torch.strided,
      device: Optional[torch.device] = None,
      requires_grad: bool = False,
  ) -> Tensor:
      if dtype is None:
          dtype = torch.get_default_dtype()
  
      _window_function_checks("general_cosine", M, dtype, layout)
  
      if M == 0:
          return torch.empty(
              (0,),
              dtype=dtype,
              layout=layout,
              device=device,
              requires_grad=requires_grad,
          )
  
      if M == 1:
          return torch.ones(
              (1,),
              dtype=dtype,
              layout=layout,
              device=device,
              requires_grad=requires_grad,
          )
  
      if not isinstance(a, Iterable):
          raise TypeError("Coefficients must be a list/tuple")
  
      if not a:
          raise ValueError("Coefficients cannot be empty")
  
      constant = 2 * torch.pi / (M if not sym else M - 1)
  
      k = torch.linspace(
          start=0,
          end=(M - 1) * constant,
          steps=M,
          dtype=dtype,
          layout=layout,
          device=device,
          requires_grad=requires_grad,
      )
  
      a_i = torch.tensor(
          [(-1) ** i * w for i, w in enumerate(a)],
          device=device,
          dtype=dtype,
          requires_grad=requires_grad,
      )
      i = torch.arange(
          a_i.shape[0],
          dtype=a_i.dtype,
          device=a_i.device,
          requires_grad=a_i.requires_grad,
      )
      return (a_i.unsqueeze(-1) * torch.cos(i.unsqueeze(-1) * k)).sum(0)
  
file_path: pytorch/torch/signal/windows/windows.py
imports: from typing import Optional, Iterable
  import torch
  from math import sqrt
  from torch import Tensor
  from torch._torch_docs import factory_common_args, parse_kwargs, merge_dicts
label_desc: Use image node_id 11 for calling a global function with example usage: general_cosine(M) and returns: unknown, torch, torch